Understanding The Concept Of Big Data
Big data is an information technology term defined as the amount of data that gets more bulky, complex, and fast moving that it is very difficult to handle through normal database management tools. Such issues related to big data arise regularly in different fields, such as meteorology or business intelligence, to process the available bulky data for getting the solution of the problems. Thus, the data gets bulkier and newer tools and platforms are required to handle such issues pertaining to the big data.
Big data is not a very old concept in information technology. This concept evolved from the three fundamental attributes of the blasting nature of data: rapidly increasing volume of data, need of fast processing velocity, and a variety of data types.
The increase in data volume is so fast that it is astonishing to find out that we create more than 2.5 quintillion bytes of data every single day, according to IBM research. It does not stop at this growth rate; every second the growth rate of data increase is faster than the previous one. Comparatively, we create more data during every new second than in the previous one. This is very interesting as it means that 90 percent of today’s total data was created in the last two years! This trend will prevail in the the future too. As per normal trends since last three decades, the data volume doubles after every three years or so.
Exponentially increasing data in structured or unstructured forms are text, videos, call detail records of mobile communications, as well as other forms of telephone and data calls, camera and telescope surveillance of different activities on the globe and beyond, sales and purchase transaction records, social websites, GPS navigation, and other online services to name a few.
Mobile phone and other telecommunication companies are a big source of data increase through their call detail records or CDRs. CDRs are used for billing and other legal and commercial purposes. It is estimated that more than 500 million calls are originated and terminated from one telephone device to another. The records are made at both ends, thus increasing the volume of data to many terabytes.
Big data has yet to be defined in terms of volumes and velocities; but normally, it ranges from a few dozen terabytes to many petabytes. It depends on the nature of the data and its velocity to process in and process out of the main storage of data.
Normally applied techniques of database management systems are not capable to process and handle such huge volumes and complexity of the data. Therefore, newer mechanisms are being implemented to handle big data. Exceptional and high end technologies for processing big data are data mining grids, massively parallel processing databases, cloud computing platforms, distributed file systems, scalable storage systems, and the Internet.
Rational database management systems are the most efficient forms of rational database handling that work on the basis of relational tables of data and thus make it faster to access and process the data in different ways. There are very few massively parallel processing databases that can handle petabytes of data efficiently, taking into account the complexity of big data processing.
IT engineers enjoy the challenge of exploring big data; the complexity of the problem provides an opportunity to technical thinkers and leaders to develop newer ideas for tackling the issues that pose a threat to the smooth operation of IT processes. Bigger companies like IBM, Oracle, Microsoft, and Siemens are investing more money in research and development for better solutions to these problems.
Big data will not only keep increasing its volume but the expected increase is much more than present trend. Many people in the world have still not started using the Internet; the big data will increase drastically once those people start using the newer technologies and the Internet. This means the demand of data use of the existing users is increasing very rapidly. Smartphones and wireless technologies are fuelling the rapid swelling up of big data of the world. This only makes more fun and challenging for IT engineers to explore the concept of big data and develop new technologies.
By Walter Bailey